Identifying a Three-Gene Signature and Associated Drugs for Hepatitis B Virus-Related Hepatocellular Carcinoma Using Comprehensive Bioinformatics Analysis

Tan, Yan; Zhang, Meiling; Chen, Xiaoshan; Deng, Yongyue

doi:10.1620/tjem.2022.j069

Cited by 3 publications

(2 citation statements)

References 51 publications

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“…Among the PPI network of DEGs, ten genes (BUB1, BUB1B, CCNA2, CCNB1, CCNB2, CDC20, CDK1, NCAPG, KIF11, TOP2A) were identified as hub genes. This result is partially consistent with the finding of Yan Tan et al (Tan et al 2022). Four of these hub genes (BUB1B, CCNB1, CDK1 and TOP2A) were also identified as the hub genes in the network of upregulated genes in Hepatitis B virus-related HCC (Tan et al 2022).…”

Section: Discussionsupporting

confidence: 93%

“…This result is partially consistent with the finding of Yan Tan et al (Tan et al 2022). Four of these hub genes (BUB1B, CCNB1, CDK1 and TOP2A) were also identified as the hub genes in the network of upregulated genes in Hepatitis B virus-related HCC (Tan et al 2022). Interestingly, all these hub genes were upregulated in HCC tissues and have been reported to play roles in the cell cycle process.…”

Section: Discussionsupporting

confidence: 93%

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The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma

Zhou

Zhang

Deng

et al. 2022

Tohoku J. Exp. Med.

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Hepatocellular carcinoma (HCC) is one of the most common and lethal types of cancer. This study aimed to identify the expression regulatory network and a prognostic signature of HCC.RNA-seq data from The Cancer Genome Atlas were used to identify the differentially expressed genes (DEGs) between HCC and normal liver tissues. DEGs were subjected to the construction of protein-protein interaction (PPI) network and enrichment analysis of Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The results showed that most of the DEGs were enriched in the cell cycle pathway, and the top 10 hub genes in the PPI network belong to the cell cycle pathway. A ceRNA network was constructed using starBase database, including one lncRNA (SNHG1), seven miRNAs (miR-195-5p, miR-199a-3p, miR-199a-5p, miR-199b-3p, miR-383-5p, miR-424-5p and miR-654-3p) and six of the top 10 hub genes (BUB1,CCNA2, CCNB1, KIF11, NCAPG, and TOP2A).In vitro experiments showed that knockdown of SNHG1 in the HCC cell lines (Huh7 and HepG2) decreased the expression of the six hub genes and cell viability, leading to cell cycle arrest at the G1 phase. These findings indicate that SNHG1 promotes cell proliferation by regulating cell cycle-related genes as a ceRNA. Additionally, Kaplan-Meier's survival and multivariate Cox regression analysis identified a prognostic signature of seven genes (including SNHG1 and the six SNHG1-regulated hub genes) for overall survival (OS) of HCC patients. In conclusion, this study identified a novel regulatory network in HCC and a potential independent prognostic factor for OS of HCC patients.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 93%

The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma

Zhou

Zhang

Deng

et al. 2022

Tohoku J. Exp. Med.

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Investigating key genes and biological pathways for therapeutic drug compound identification and survival analysis of chronic lymphocytic leukemia and hepatitis B associated hepatocellular carcinoma using system biology approach

Rabbi,

Islam,

Akhter

et al. 2024

Netw Model Anal Health Inform Bioinforma

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KNL1 is a prognostic and diagnostic biomarker related to immune infiltration in patients with uterine corpus endometrial carcinoma

Huang

et al. 2023

Front. Oncol.

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BackgroundThe incidence and mortality of uterine corpus endometrial carcinoma (UCEC) are increasing yearly. There is currently no screening test for UCEC, and progress in its treatment is limited. It is important to identify new biomarkers for screening, diagnosing and predicting the outcomes of UCEC. A large number of previous studies have proven that KNL1 is crucial in the development of lung cancer, colorectal cancer and cervical cancer, but there is a lack of studies about the role of KNL1 in the development of UCEC.MethodsThe mRNA and protein expression data of KNL1 in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and UALCAN databases and related clinical data were used to analyze the expression differences and clinical correlations of KNL1 in UCEC. A total of 108 clinical samples were collected, and the results of bioinformatics analysis were verified by immunohistochemistry. KNL1 and its related differentially expressed genes were used to draw a volcano map, construct a PPI protein interaction network, and perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and immune infiltration analysis to predict the function of KNL1 during UCEC progression. The prognostic data of TCGA and 108 clinical patients were used to analyze the correlation of KNL1 expression with the survival of patients, and KM survival curves were drawn. The UCEC cell lines Ishikawa and Hec-1-A were used to verify the function of KNL1.ResultsKNL1 is significantly overexpressed in UCEC and is associated with a poor prognosis. KNL1 overexpression is closely related to cell mitosis, the cell cycle and other functions and is correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade and other characteristics of UCEC patients. Knockdown of KNL1 expression in UCEC cell lines can inhibit their proliferation, invasion, metastasis and other phenotypes.ConclusionKNL1 is a prognostic and diagnostic biomarker associated with immune evasion in patients with UCEC.

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Identifying a Three-Gene Signature and Associated Drugs for Hepatitis B Virus-Related Hepatocellular Carcinoma Using Comprehensive Bioinformatics Analysis

Abstract: Identifying a three-gene signature and associated drugs for Hepatitis B Virusrelated Hepatocellular Carcinoma using comprehensive bioinformatics analysis

Cited by 3 publications

References 51 publications

The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma

The SNHG1-Centered ceRNA Network Regulates Cell Cycle and Is a Potential Prognostic Biomarker for Hepatocellular Carcinoma

Investigating key genes and biological pathways for therapeutic drug compound identification and survival analysis of chronic lymphocytic leukemia and hepatitis B associated hepatocellular carcinoma using system biology approach

KNL1 is a prognostic and diagnostic biomarker related to immune infiltration in patients with uterine corpus endometrial carcinoma

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